{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "# Plotter"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "**Author:** [Leah Nguyen](https://github.com/ndleah)"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Description"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "An automation program to plot data with different visualisations by user selections"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Requirement"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "source": [
    "!pip install chart_studio\r\n",
    "!pip install cufflinks"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Requirement already satisfied: chart_studio in c:\\users\\leah nguyen\\anaconda3\\lib\\site-packages (1.1.0)\n",
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     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Import libraries"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import chart_studio.plotly as pl\n",
    "import plotly.offline as po\n",
    "import cufflinks as cf"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "Setting cufflinks to offline mode"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "source": [
    "po.init_notebook_mode(connected = True)\n",
    "cf.go_offline()"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-2.2.0.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-2.2.0.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {}
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Define automation functions"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    " Differentcreate data options using function ```createdata```"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "source": [
    "def createdata(data):\r\n",
    "    if(data == 1):\r\n",
    "        x = np.random.rand(100, 5)\r\n",
    "        df1 = pd.DataFrame(x, columns = ['A', 'B', 'C', 'D', 'E'])\r\n",
    "    elif(data == 2):\r\n",
    "        x = [0,0,0,0,0]\r\n",
    "        r1 = [0,0,0,0,0]\r\n",
    "        r2 = [0,0,0,0,0]\r\n",
    "        r3 = [0,0,0,0,0]\r\n",
    "        r4 = [0,0,0,0,0]\r\n",
    "        print('Enter the values for columns ')\r\n",
    "        i = 0\r\n",
    "        for i in (0,1,2,3,4):\r\n",
    "            x[i] = input()\r\n",
    "            i = i + 1\r\n",
    "        print('Enter the values for first row ')\r\n",
    "        i = 0\r\n",
    "        for i in (0,1,2,3,4):\r\n",
    "            r1[i] = int(input())\r\n",
    "            i = i + 1\r\n",
    "        print('Enter the values for second row ')\r\n",
    "        i = 0\r\n",
    "        for i in (0,1,2,3,4):\r\n",
    "            r2[i] = int(input())\r\n",
    "            i = i + 1\r\n",
    "        print('Enter the values for third row ')\r\n",
    "        i = 0\r\n",
    "        for i in (0,1,2,3,4):\r\n",
    "            r3[i] = int(input())\r\n",
    "            i = i + 1\r\n",
    "        print('Enter the values for forth row ')\r\n",
    "        i = 0\r\n",
    "        for i in (0,1,2,3,4):\r\n",
    "            r4[i] = int(input())\r\n",
    "            i = i + 1\r\n",
    "        df1= pd.DataFrame([r1, r2, r3, r4], columns = x)\r\n",
    "    elif(data == 3):\r\n",
    "        file = input('Enter the file name ')\r\n",
    "        x = pd.read_csv(file)\r\n",
    "        df1 = pd.DataFrame(x)\r\n",
    "    else:\r\n",
    "        print('Dataframe creation failed, please enter in between 1 to 3 and try ')\r\n",
    "    return df1"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "Plotting all columns option using function ```plotter```"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "source": [
    "def plotter(plot):\r\n",
    "    if(plot == 1):\r\n",
    "        finalplot = df1.iplot(kind = 'scatter')\r\n",
    "    elif(plot == 2):\r\n",
    "        finalplot = df1.iplotfinalplot = df1.iplot(kind = 'scatter', mode = 'markers', symbol = 'x', colorscale = 'paired')\r\n",
    "    elif(plot == 3):\r\n",
    "        finalplot = df1.iplot(kind = 'bar')\r\n",
    "    elif(plot == 4):\r\n",
    "        finalplot = df1.iplot(kind = 'hist')\r\n",
    "    elif(plot == 5):\r\n",
    "        finalplot = df1.iplot(kind = 'box')\r\n",
    "    elif(plot == 6):\r\n",
    "        finalplot = df1.iplot(kind = 'surface')\r\n",
    "    else:\r\n",
    "        finalplot = print('Select only between 1 to 7')\r\n",
    "    return finalplot"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "Plotting by selecting specific columns using function ```plotter2```"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "source": [
    "def plotter2(plot):\r\n",
    "    col = input('Enter the number of columns you want to plot by selecting only 1, 2 or 3')\r\n",
    "    col = int(col)\r\n",
    "    if(col == 1):\r\n",
    "        coln = input('Enter the column you want to plot by selecting any column from dataframe head')\r\n",
    "        if(plot == 1):\r\n",
    "            finalplot = df1[coln].iplot(kind = 'scatter')\r\n",
    "        elif(plot == 2):\r\n",
    "            finalplot = df1[coln].iplot(kind = 'scatter', mode = 'markers', symbol = 'x', colorscale = 'paired')\r\n",
    "        elif(plot == 3):\r\n",
    "            finalplot = df1[coln].iplot(kind = 'bar')\r\n",
    "        elif(plot == 4):\r\n",
    "            finalplot = df1[coln].iplot(kind = 'hist')\r\n",
    "        elif(plot == 5):\r\n",
    "            finalplot = df1[coln].iplot(kind = 'box')\r\n",
    "        elif(plot == 6 or plot == 7):\r\n",
    "            finalplot = print(\"Bubble plot and surface plot require more than one column arguements\")\r\n",
    "        else:\r\n",
    "            finalplot = print('Select only between 1 to 7')               \r\n",
    "    elif(col == 2):\r\n",
    "        print('Enter the columns you want to plot by selecting from dataframe head')\r\n",
    "        x = input('First column')\r\n",
    "        y = input('Second column')\r\n",
    "        if(plot == 1):\r\n",
    "            finalplot = df1[[x, y]].iplot(kind = 'scatter')\r\n",
    "        elif(plot == 2):\r\n",
    "            finalplot = df1[[x, y]].iplot(kind = 'scatter', mode = 'markers', symbol = 'x', colorscale = 'paired')\r\n",
    "        elif(plot == 3):\r\n",
    "            finalplot = df1[[x, y]].iplot(kind = 'bar')\r\n",
    "        elif(plot == 4):\r\n",
    "            finalplot = df1[[x, y]].iplot(kind = 'hist')\r\n",
    "        elif(plot == 5):\r\n",
    "            finalplot = df1[[x, y]].iplot(kind = 'box')\r\n",
    "        elif(plot == 6):\r\n",
    "            finalplot = df1[[x, y]].iplot(kind = 'surface')\r\n",
    "        elif(plot == 7):\r\n",
    "            size = input('Please enter the size column for bubble plot')\r\n",
    "            finalplot = df1.iplot(kind = 'bubble', x=x, y=y, size=size)\r\n",
    "        else:\r\n",
    "            finalplot = print('Select only between 1 to 7')              \r\n",
    "    elif(col == 3):\r\n",
    "        print('Enter the columns you want to plot')\r\n",
    "        x = input('First column')\r\n",
    "        y = input('Second column')\r\n",
    "        z = input('Third column')\r\n",
    "        if(plot == 1):\r\n",
    "            finalplot = df1[[x, y, z]].iplot(kind = 'scatter')\r\n",
    "        elif(plot == 2):\r\n",
    "            finalplot = df1[[x, y, z]].iplot(kind = 'scatter', mode = 'markers', symbol = 'x', colorscale = 'paired')\r\n",
    "        elif(plot == 3):\r\n",
    "            finalplot = df1[[x, y, z]].iplot(kind = 'bar')\r\n",
    "        elif(plot == 4):\r\n",
    "            finalplot = df1[[x, y, z]].iplot(kind = 'hist')\r\n",
    "        elif(plot == 5):\r\n",
    "            finalplot = df1[[x, y, z]].iplot(kind = 'box')\r\n",
    "        elif(plot == 6):\r\n",
    "            finalplot = df1[[x, y, z]].iplot(kind = 'surface')\r\n",
    "        elif(plot == 7):\r\n",
    "            size = input('Please enter the size column for bubble plot')\r\n",
    "            finalplot = df1.iplot(kind = 'bubble', x=x, y=y, z=z, size=size)\r\n",
    "        else:\r\n",
    "            finalplot = print('Select only between 1 to 7')\r\n",
    "    else:\r\n",
    "        finalplot = print('Please enter only 1, 2 or 3 and try again')\r\n",
    "    return finalplot"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "User selection with plotting table using function ```main```"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "source": [
    "def main(cat):\n",
    "    if(cat == 1):\n",
    "        print('Select the type of plot you want to plot by writing 1 to 6')\n",
    "        print('1. Line Plot')\n",
    "        print('2. Scatter Plot')\n",
    "        print('3. Bar Plot')\n",
    "        print('4. Histogram')\n",
    "        print('5. Box Plot')\n",
    "        print('6. Surface Plot')\n",
    "        plot = int(input())\n",
    "        output = plotter(plot)\n",
    "    elif(cat == 2):\n",
    "        print('Select the type of plot you want to plot by writing 1 to 7')\n",
    "        print('1. Line Plot')\n",
    "        print('2. Scatter Plot')\n",
    "        print('3. Bar Plot')\n",
    "        print('4. Histogram')\n",
    "        print('5. Box Plot')\n",
    "        print('6. Surface Plot')\n",
    "        print('7. Bubble Plot')\n",
    "        plot = int(input())\n",
    "        output = plotter2(plot)\n",
    "    else:\n",
    "        print('Please enter 1 or 2 and try again')"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Scripts for code executions"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "1. User choose the way they want data to be create:"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "source": [
    "print('Select the type of data you need to plot(By writing 1, 2, or 3)')\n",
    "print('1. Random data with 100 rows and 5 columns')\n",
    "print('2. Customize dataframe with 5 colums and 4 rows')\n",
    "print('3. Upload csv/json/txt file')\n",
    "data = int(input())\n",
    "df1 = createdata(data)"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Select the type of data you need to plot(By writing 1, 2, or 3)\n",
      "1. Random data with 100 rows and 5 columns\n",
      "2. Customize dataframe with 5 colums and 4 rows\n",
      "3. Upload csv/json/txt file\n",
      "1\n"
     ]
    }
   ],
   "metadata": {
    "scrolled": true
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "2. Inspecting the first 5 rows of the dataframe using ```head()``` function:"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "source": [
    "print('Your DataFrame head is given below, check the columns to plot using cufflinks')\n",
    "df1.head()"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Your DataFrame head is given below, check the columns to plot using cufflinks\n"
     ]
    },
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "          A         B         C         D         E\n",
       "0  0.308356  0.135629  0.609048  0.540077  0.492091\n",
       "1  0.029683  0.333192  0.960456  0.436233  0.680954\n",
       "2  0.583523  0.621940  0.110303  0.420751  0.402851\n",
       "3  0.057509  0.382840  0.314781  0.626836  0.809157\n",
       "4  0.940898  0.122087  0.226713  0.265897  0.406339"
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.308356</td>\n",
       "      <td>0.135629</td>\n",
       "      <td>0.609048</td>\n",
       "      <td>0.540077</td>\n",
       "      <td>0.492091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.029683</td>\n",
       "      <td>0.333192</td>\n",
       "      <td>0.960456</td>\n",
       "      <td>0.436233</td>\n",
       "      <td>0.680954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.583523</td>\n",
       "      <td>0.621940</td>\n",
       "      <td>0.110303</td>\n",
       "      <td>0.420751</td>\n",
       "      <td>0.402851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.057509</td>\n",
       "      <td>0.382840</td>\n",
       "      <td>0.314781</td>\n",
       "      <td>0.626836</td>\n",
       "      <td>0.809157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.940898</td>\n",
       "      <td>0.122087</td>\n",
       "      <td>0.226713</td>\n",
       "      <td>0.265897</td>\n",
       "      <td>0.406339</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "execution_count": 9
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "3. Selecting the number of columns they want to plot (whole table or selected columns only):"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "source": [
    "print('What kind if plot you need, the complete data plot or columns plot')\n",
    "cat = input('Press 1 for plotting all columns or press 2 for specifying columns to plot')\n",
    "cat = int(cat)"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "What kind if plot you need, the complete data plot or columns plot\n",
      "Press 1 for plotting all columns or press 2 for specifying columns to plot1\n"
     ]
    }
   ],
   "metadata": {
    "scrolled": true
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "4. Choosing the plot types:"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "source": [
    "main(cat)"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Select the type of plot you want to plot by writing 1 to 6\n",
      "1. Line Plot\n",
      "2. Scatter Plot\n",
      "3. Bar Plot\n",
      "4. Histogram\n",
      "5. Box Plot\n",
      "6. Surface Plot\n",
      "1\n"
     ]
    },
    {
     "output_type": "display_data",
     "data": {
      "text/html": [
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